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Talend Data Integration

Talend Data Integration

Overview

What is Talend Data Integration?

The Talend Integration Suite, from Talend, is a set of tools for data integration.

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Pricing

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What is Talend Data Integration?

The Talend Integration Suite, from Talend, is a set of tools for data integration.

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

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Product Demos

3. Talend Data Integration demo for Error Handling

YouTube

Talend ETL Tool Tutorial For Beginners and Advanced | Online Training | Venkat| +91-9538160185

YouTube

Talend Training | Talend Real Time Projects #TalendTechSolutions #TalendDi

YouTube
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Features

Data Source Connection

Ability to connect to multiple data sources

8.2
Avg 8.4

Data Transformations

Data transformations include calculations, search and replace, data normalization and data parsing

8.8
Avg 8.2

Data Modeling

A data model is a diagram or flowchart that illustrates the relationships between data

7.9
Avg 8.0

Data Governance

Data governance is the practise of implementing policies defining effective use of an organization's data assets

7.8
Avg 8.3
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Product Details

What is Talend Data Integration?

Talend Data Integration Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

The Talend Integration Suite, from Talend, is a set of tools for data integration.

Reviewers rate Connect to traditional data sources and Simple transformations and Complex transformations highest, with a score of 8.8.

The most common users of Talend Data Integration are from Small Businesses (1-50 employees).
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Comparisons

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Reviews From Top Reviewers

(1-2 of 2)

Talend OpenStudio building your EDW at $0 cost

Rating: 10 out of 10
October 06, 2016
Vetted Review
Verified User
Talend Data Integration
4 years of experience
We use the big data edition of Talend Integration Suite. It is used by the Business Intelligence department for extract transform load (ETL). There are more than 400 jobs that pull data or push data from various sources. Talend is used to load data into the enterprise data warehouse. (EDW). I use the big data edition to pull data from hive cluster. There are complex sources like highly nested JSON and XML that can be easily parsed using Talend components. The best thing I like about Talend is the ease of use/debug and ease of deployment. Behind the scenes it uses Java coding, so whatever you do in the interface can be easily visible under code. Packaging and deployment of code is easy too in any environment (Windows or Mac or Linux) with any version of Java compatibility.
  • JSON parsing, if you are into highly nested JSON object parsing Talend has the ability to display the structure of JSON and allows you to define the extraction logic in the metadata. Same with XML source.
  • Customization, For mostly all ETL work you will have a component in Talend. And in case you have a very specific requirement you can end up easily designing a custom component that you can code and reuse and share with others.
  • Talend has a connectivity option to almost all the databases (relational or NOSQ)L and sources available. It also has generic JDBC/ ODBC drivers in case you need it.
  • I like the ease of deployment across environment (DEV and PROD) with the use of context variables.
Cons
  • The Talend Administration Console TAC is a great place to schedule and monitor your jobs. Probably the interface can be improved.
Talend as an ETL tool is robust and flexible because of the transparency of the behind the scene Java code. Developers can debug and optimize the code easily because of visibility. The big data component of talend makes it the IDE for working with file formats like JSON and log files.

Talend gives the ability to pull data using WSDL/API and also to make data available as REST API. Talend jobs are platform independent and can be deployed easily. IDE is eclipse based.
Data Source Connection (2)
100%
10.0
Connect to traditional data sources
100%
10.0
Connecto to Big Data and NoSQL
100%
10.0
Data Transformations (2)
100%
10.0
Simple transformations
100%
10.0
Complex transformations
100%
10.0
Data Modeling (5)
100%
10.0
Data model creation
100%
10.0
Metadata management
100%
10.0
Business rules and workflow
100%
10.0
Collaboration
100%
10.0
Testing and debugging
100%
10.0
Data Governance (2)
100%
10.0
Integration with data quality tools
100%
10.0
Integration with MDM tools
100%
10.0
  • The product provides a cost effective solution to integrate salesforce data source
  • With a single big data license customers can develop and deploy a full EDW solution
  • Administration and installation

There are code building and code conversions internally in most of these ETL tools. The repository is an overhead in the ETL process. There may be a need for a full-time administrator to manage deployments and monitor jobs. With Talend, it seems to be transparent with the pure JAVA/PERL code. You have the ability to easily customize your code. It has support for big data integration. The data quality/ MDM tools can be easily integrated with Talend ETL.

The license cost is low compared to other ETL tools. With the new version of talend cloud-based hosted deployment is also available. An overall full featured open source version of Talend studio is available that can be used at zero cost with some amount of scripting to automate tasks.

I was able to replace SSIS with a zero cost Talend open studio deployment with shell scripting and CRON scheduling.

No
  • Price
  • Product Features
  • Product Usability
  • Prior Experience with the Product
In my previous company, I used Talend open studio to replace SSIS with a zero cost ETL tool to build our EDW. Since we worked with the open studio community edition, we got a lot of opportunities to look under the hood to make custom changes and to implement and automate a few features. In the process, we explored the full product in and out and came to know the pros and cons of the product. That helped me to make a decision in my next assignment to go for Talend. It overall helped me to design and develop ETL jobs with quick turn around time - this time with the licensed Talend Big data integration tool.
I think I would simply go with Talend. Over a period of time, it has grown up as an enterprise product with the open source blend. The new big data solutions connectors are easily available or customized in talend. The parallel execution multi-threaded execution option helps with running jobs in parallel.
Talend Joblets support speedy development of jobs using templates. The documentation option dumps the entire job as HTML for technical review and readability.
Yes
for a large scale deployment (700+ jobs). Support is usually helpful when you are doing a POC for new development projects and want to find out the compatibility of tools. It also covers upgrades to scale your environment periodically. Access to knowledge and forums also helps new developers speed up the job building process.
Good support, specially when it relates to PROD environment. The support team has access to the product development team. Things are internally escalated to development team if there is a bug encountered. This helps the customer to get quick fix or patch designed for problem exceptions. I have also seen support showing their willingness to help develop custom connector for a newly available cloud based big data solution
No

An excellent data integration tool

Rating: 9 out of 10
September 28, 2016
JC
Vetted Review
Verified User
Talend Data Integration
6 years of experience
Talend is used to build a corporate data warehouse solution which centralizes all relevant company intel into a single repository. Talend is used for development only by the IT department (as expected) but the information it gathers is used for the whole company. The main problem which talend addresses is to unify different sources of intel by retrieving data from databases, files, web services, the internet, etc.
  • Reading for multiple sources: Any modern Database, Files, WebServices, etc.
  • Monitoring and scheduling task dependencies for data loading purposes.
  • Really useful to design a Data Warehouse, thanks to its built in components for design patterns like SCD, etc.
  • It's also useful to publish data interfaces via WebServices or REST.
  • Good and high qualified support team.
  • Connecting to various databases from classic Relational (MSSQL, Oracle, MySQL, etc.) to No-SQL Databases.
  • Well documented.
  • Community which provides plugins, etc.
Cons
  • Installation process of Integration Suite platform.
  • JAVA memory management. It's easy to get a memory overhead error, and you have to modify configuration files to increase memory manually.
  • Migration process.
It's perfect for data warehouse implementation.
Data Source Connection (2)
95%
9.5
Connect to traditional data sources
100%
10.0
Connecto to Big Data and NoSQL
90%
9.0
Data Transformations (2)
90%
9.0
Simple transformations
100%
10.0
Complex transformations
80%
8.0
Data Modeling (5)
84%
8.4
Data model creation
90%
9.0
Metadata management
90%
9.0
Business rules and workflow
80%
8.0
Collaboration
90%
9.0
Testing and debugging
70%
7.0
Data Governance (2)
90%
9.0
Integration with data quality tools
90%
9.0
Integration with MDM tools
90%
9.0
  • Easy to build complex data transformations.
  • Licensing model isn't that flexible.
  • Memory mangement for huge volumes of information. You have to modify ETL designs to handle it properly.
Compared to Microsoft SQL Server Integration Services (SSIS) talend gives developers much more tools and flexibility in order to achieve different ETL processes. For instance, SSIS, separates processing from data management, and Talend mixes both stages so that you can perform complex processes like iterating sub-jobs for each data row. It also provides a huge component list compared to SSIS which allows retrieving and saving data from many various sources. The administration part is also wider than what is offered from SSIS. In other words, SSIS is like a toy compared to Talend Integration's capabilities.
When comparing Talend with Kettle (Pentaho) it's is easy to find similarities because they are both similar tools. In my experience, I'd rather [use] Talend because, in my opinion, it is more focused at data management. Kettle is a component provided from a wider BI tool, and Pentaho is not only focused at data management. I also found Talend gives better performance and manages connection sockets better than Kettle.
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